Bridge-specific flood risk assessment of transport networks using GIS and remotely sensed data

A novel framework for the expedient assessment of flood risk to transportation networks focused on the response of the most critical and vulnerable infrastructure assets, the bridges, is developed, validated and applied. Building upon the recent French guidelines on scour risk (CEREMA, 2019), this paper delivers a thorough methodology, that incorporates three key, risk parameters: (i) the hydrodynamic loading, a hazard component of equal significance to scour, for the assessment of hazard; (ii) the correlation of select scour indicators with a new index relating to flow velocity, a primary measure of the adverse impacts of flow–structure interaction, enabling a more accurate and automated, assessment of bridge susceptibility to scour; (iii) the use of a new, comprehensive indicator, namely the Indicator of Flood Hazard Intensity (IFHI) which incorporates, in a simple yet efficient way, the key parameters controlling the severity of flood impact on bridges, namely flow velocity, floodwater height, flow obstruction, and sediment type. The framework is implemented for the analysis of flood risk in a case study area, considering an inventory of 117 bridges of diverse construction characteristics, which were affected by a major flood that impacted Greece in September 2020. The reliability of the method is validated against an extensive record of inspected and documented bridge damages. Regional scale analysis is facilitated by the adoption of the Multi-Criteria Decision-Making method for flood hazard indexing, considering geomorphological, meteorological, hydrological, and land use/cover data, based on the processing of remotely sensed imagery and openly available geospatial datasets in GIS. Fig. A new framework for a bridge-specific assessment of flood risk in transport networks. [Display omitted] •MCDM-based characterization of hydraulic actions on bridges has been incorporated in a regional risk assessment framework.•The method is efficient for a bridge-specific characterization of flood hazard and predicts realistically the damage level.•Extensive validation has been based on field data involving 16 bridges with varying characteristics and levels of damage.•A network-scale implementation has been based on publicly available datasets and remotely sensed imagery processed in GIS.•Identification of assets worthy of prioritization in climate adaptation strategies in a high-risk area of Greece.